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Regression Analysis of Multivariate Fractional Data

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Author Info

  • José M.R. Murteira

    ()
    (Faculdade de Economia, Universidade de Coimbra, and CEMAPRE)

  • Joaquim J.S. Ramalho

    ()
    (Departamento de Economia and CEFAGE-UE, Universidade de Évora)

Abstract

The present article discusses alternative regression models and estimation methods for dealing with multivariate fractional response variables. Both conditional mean models, estimable by quasi-maximum likelihood, and fully parametric models (Dirichlet and Dirichletmultinomial), estimable by maximum likelihood, are considered. A new parameterization is proposed for the parametric models, which accommodates the most common specifications for the conditional mean (e.g., multinomial logit, nested logit, random parameters logit, dogit). The text also discusses at some length the specification analysis of fractional regression models, proposing several tests that can be performed through artificial regressions. Finally, an extensive Monte Carlo study evaluates the finite sample properties of most of the estimators and tests considered.

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Bibliographic Info

Paper provided by University of Evora, CEFAGE-UE (Portugal) in its series CEFAGE-UE Working Papers with number 2013_05.

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Length: 44 pages
Date of creation: 2013
Date of revision:
Handle: RePEc:cfe:wpcefa:2013_05

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Related research

Keywords: Multivariate fractional data; Quasi-maximum likelihood estimator; Dirichlet regression; Regression-based specification tests.;

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  1. Donald W.K. Andrews, 1999. "Testing When a Parameter Is on the Boundary of the Maintained Hypothesis," Cowles Foundation Discussion Papers 1229, Cowles Foundation for Research in Economics, Yale University.
  2. Chotikapanich, Duangkamon & Griffiths, William E, 2002. "Estimating Lorenz Curves Using a Dirichlet Distribution," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 290-95, April.
  3. Andrew Chesher & J. M. C. Santos Silva, 2002. "Taste Variation in Discrete Choice Models," Review of Economic Studies, Oxford University Press, vol. 69(1), pages 147-168.
  4. Mahdi Alkhamisi & Ghadban Khalaf & Ghazi Shukur, 2008. "The effect of fat-tailed error terms on the properties of systemwise RESET test," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(1), pages 101-113.
  5. Considine, Timothy J & Mount, Timothy D, 1984. "The Use of Linear Logit Models for Dynamic Input Demand Systems," The Review of Economics and Statistics, MIT Press, vol. 66(3), pages 434-43, August.
  6. Gaundry, Marc J. I. & Dagenais, Marcel G., 1979. "The dogit model," Transportation Research Part B: Methodological, Elsevier, vol. 13(2), pages 105-111, June.
  7. Dubin, Jeffrey A., 2007. "Valuing intangible assets with a nested logit market share model," Journal of Econometrics, Elsevier, vol. 139(2), pages 285-302, August.
  8. Fry, Jane M. & Fry, Tim R. L. & McLaren, Keith R., 1996. "The stochastic specification of demand share equations: Restricting budget shares to the unit simplex," Journal of Econometrics, Elsevier, vol. 73(2), pages 377-385, August.
  9. David Giles & Andrea Keil, 1997. "Applying the RESET test in allocation models: a cautionary note," Applied Economics Letters, Taylor & Francis Journals, vol. 4(6), pages 359-363.
  10. Silvia Ferrari & Francisco Cribari-Neto, 2004. "Beta Regression for Modelling Rates and Proportions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(7), pages 799-815.
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Cited by:
  1. Esmeralda Ramalho & Joquim Ramalho, 2014. "Convenient links for the estimation of hedonic price indexes:the case of unique, infrequently traded assets," CEFAGE-UE Working Papers 2014_01, University of Evora, CEFAGE-UE (Portugal).
  2. Pandit, Mahesh & Paudel, Krishna P. & Hinson, Roger A., 2013. "Market Channel Analysis of Ornamental Plants using Clustering Procedures," 2013 Annual Meeting, February 2-5, 2013, Orlando, Florida 143067, Southern Agricultural Economics Association.

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